
The 2 standard deviation rule: at least 75% of  The addition rule of probability is used to find: the
all the values will always fall within 2 s.d of the union of 2 or more events
mean

The 3 standard deviation rule:
At least 88.9% of all the values w
State
MA
NY
NJ
NC
DC
MD
VA
% of Brand
44.67
21.71
1.88
0.84
26.30
1.67
2.92
% of Category
29.52
30.20
5.62
2.14
25.96
3.52
3.04
BDI
151.32
71.88
33.45
39.25
101.30
47.44
96.05
BDI table and the areas Zipcar should focus its marketing effort on:
1. BDI =
Analysis of Variance
Chapter 12
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
6.
List the characteristics of the F distribution.
Determine whether the variances of two populations are
equal.
Discuss the general idea of analysis of
Sampling Methods and
the Central Limit Theorem
Chapter 8
Prof. Bongsik Shin
Management Information Systems
GOALS
Explain why a sample is often the only feasible way
to learn something about a population.
Describe sampling methods.
Define sampling error.
D
Describing Data:
Displaying and Exploring Data
Chapter 4
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
Compute and understand quartiles and
percentiles.
Construct and interpret box plots.
Compute and understand the coefficient of
Discrete Probability Distributions
Chapter 6
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
Probability distribution and random variable.
Distinguish between discrete and continuous
probability distributions.
mean, variance, and st
Twosample Tests of Hypothesis
Chapter 11
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
Conduct a test of difference between two independent
population means.
Conduct a test of difference between two population
proportions.
Conduct a
One Sample Tests of Hypothesis
Chapter 10
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
Define a hypothesis and hypothesis testing.
Distinguish between a onetailed and a twotailed
test of hypothesis.
Conduct a test of hypothesis
Describing Data:
Numerical Measures
Chapter 3
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
6.
arithmetic mean, weighted mean, median, and mode.
measure of location.
symmetric and skewed distributions.
range, variance, and standar
Continuous Probability
Distributions
Chapter 7
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
6.
Mean and the standard deviation for a uniform
distribution.
Compute probabilities by using the uniform distribution.
List the characte
Correlation and Linear
Regression
Chapter 13
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
Understand and interpret dependent and independent
variable.
2.
Calculate and interpret the coefficient of correlation and
the coefficient of determina
Estimation and Confidence
Intervals
Chapter 9
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
6.
Define a point estimate.
Define level of confidence.
Construct a confidence interval for the population
mean with known population stan
Describing Data:
Frequency Tables, Frequency
Distributions, and Graphic Presentation
Chapter 2
Prof. Bongsik Shin
Management Information Systems
GOALS
1.
2.
3.
4.
5.
Bar chart and Pie Chart
Frequency distribution
Histograms
Frequency polygons
Cumulative f
1.
2.
which of the following measurement is most influenced by extreme cases? MEAN
About which measure of central tendency are the sum of the deviations always equal to zero?
MEAN
3.
4.
Measure by percentile point? MEDIAN
MODE: associated with nominal lev